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Volumn , Issue , 2013, Pages 1185-1195

Supervised learning of complete morphological paradigms

Author keywords

[No Author keywords available]

Indexed keywords

DATA DRIVEN; END-TO-END SYSTEMS; LEARN+; LEXICAL ITEMS; PART OF SPEECH; SEQUENCE MODELS; TRANSFORMATION RULES;

EID: 84905693352     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (130)

References (32)
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    • Partially supervised learning of morphology with stochastic transducers
    • Tokyo, Japan
    • Alexander Clark. 2001. Partially Supervised Learning of Morphology with Stochastic Transducers. In Proceedings of Natural Language Processing Pacific Rim Symposium, pages 341-348, Tokyo, Japan.
    • (2001) Proceedings of Natural Language Processing Pacific Rim Symposium , pp. 341-348
    • Clark, A.1
  • 3
    • 33846987588 scopus 로고    scopus 로고
    • Unsupervised Models for Morpheme Segmentation and Morphology Learning
    • Feb
    • Mathias Creutz and Krista Lagus. 2007. Unsupervised Models for Morpheme Segmentation and Morphology Learning. ACM Transactions on Speech and Language Processing, 4(1):3:1-3:34, Feb.
    • (2007) ACM Transactions on Speech and Language Processing , vol.4 , Issue.1 , pp. 31-334
    • Creutz, M.1    Lagus, K.2
  • 7
    • 80053262881 scopus 로고    scopus 로고
    • Discovering morphological paradigms from plain text using a dirichlet process mixture model
    • Edinburgh, Scotland, UK
    • Markus Dreyer and Jason Eisner. 2011. Discovering Morphological Paradigms from Plain Text Using a Dirichlet Process Mixture Model. In Proceedings of Empirical Methods in Natural Language Processing, pages 616-627, Edinburgh, Scotland, UK.
    • (2011) Proceedings of Empirical Methods in Natural Language Processing , pp. 616-627
    • Dreyer, M.1    Eisner, J.2
  • 10
    • 0041079008 scopus 로고    scopus 로고
    • Unsupervised learning of the morphology of a natural language
    • June
    • John Goldsmith. 2001. Unsupervised Learning of the Morphology of a Natural Language. Computational Linguistics, 27(2):153-198, June.
    • (2001) Computational Linguistics , vol.27 , Issue.2 , pp. 153-198
    • Goldsmith, J.1
  • 11
    • 67349278780 scopus 로고    scopus 로고
    • A bayesian framework for word segmentation: Exploring the effects of context
    • Sharon Goldwater, Thomas L. Griffiths, and Mark Johnson. 2009. A Bayesian Framework for Word Segmentation: Exploring the Effects of Context. Cognition, 112(1):21-54.
    • (2009) Cognition , vol.112 , Issue.1 , pp. 21-54
    • Goldwater, S.1    Griffiths, T.L.2    Johnson, M.3
  • 13
    • 0022959142 scopus 로고
    • Dynamically expanding context, with application to the correction of symbol strings in the recognition of continuous speech
    • Teuvo Kohonen. 1986. Dynamically Expanding Context, With Application to the Correction of Symbol Strings in the Recognition of Continuous Speech. In Proceedings of the International Conference on Pattern Recognition.
    • (1986) Proceedings of the International Conference on Pattern Recognition
    • Kohonen, T.1
  • 17
    • 33646887390 scopus 로고
    • On the limited memory BFGS method for large scale optimization
    • December
    • Dong C. Liu and Jorge Nocedal. 1989. On the limited memory BFGS method for large scale optimization. Mathematical Programming, 45(3):503-528, December.
    • (1989) Mathematical Programming , vol.45 , Issue.3 , pp. 503-528
    • Liu, D.C.1    Nocedal, J.2
  • 20
    • 33744981648 scopus 로고    scopus 로고
    • Learning stochastic edit distance: Application in handwritten character recognition
    • September
    • Jose Oncina and Marc Sebban. 2006. Learning Stochastic Edit Distance: Application in Handwritten Character Recognition. Pattern Recognition, 39(9):1575-1587, September.
    • (2006) Pattern Recognition , vol.39 , Issue.9 , pp. 1575-1587
    • Oncina, J.1    Sebban, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.